Triple
T4633137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabeul Governorate |
E101463
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Korba |
E417301
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Korba | Statement: [Nabeul Governorate, hasCity, Korba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korba Context triple: [Nabeul Governorate, hasCity, Korba]
-
A.
Korba
Korba is an industrial city in the Indian state of Chhattisgarh, known primarily for its coal mining and power generation industries.
-
B.
Korba
chosen
Korba is a coastal town in northeastern Tunisia known for its beaches, agriculture, and role as a local commercial center.
-
C.
Raigarh
Raigarh is a regional dialect of the Chhattisgarhi language spoken in and around the Raigarh area of the Indian state of Chhattisgarh.
-
D.
Narsinghpur
Narsinghpur is a city and administrative center in central India known for its agricultural economy, particularly sugarcane and pulses, within the state of Madhya Pradesh.
-
E.
Contai
Contai is a coastal town in eastern India known as a regional commercial and transport hub in the Purba Medinipur district of West Bengal.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a5d0de881909baacc5b991f5b53 |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfac317248190a8886d59d2242acb |
completed | March 21, 2026, 1:56 a.m. |
Created at: March 20, 2026, 1:13 p.m.